package test06;

/**
 * 量化压缩策略
 */
public class QuantizationStrategy implements InferenceOptimizationStrategy {
    private String quantizationLevel = "INT8";

    @Override
    public Tensor[] optimizeInference(Model model, RequestData[] requests) {
        System.out.println("🔧 应用量化策略: " + quantizationLevel);

        // 模拟量化过程
        System.out.println("   - 将模型从FP32转换为" + quantizationLevel);
        System.out.println("   - 减少内存占用和计算开销");

        // 执行量化后的推理
        Tensor[] preprocessedInputs = preprocessInputs(requests);
        return model.forward(preprocessedInputs);
    }

    private Tensor[] preprocessInputs(RequestData[] requests) {
        Tensor[] inputs = new Tensor[requests.length];
        for (int i = 0; i < requests.length; i++) {
            // 模拟输入预处理
            inputs[i] = new Tensor(new float[]{1.0f, 0.0f, 0.5f}, new int[]{1, 3});
        }
        return inputs;
    }

    public void setQuantizationLevel(String level) {
        this.quantizationLevel = level;
        System.out.println("设置量化级别: " + level);
    }
}
